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82 results for "summarize"
summarize
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
openclaw
summarize
总结或转录URL、YouTube/视频、播客、文章、文字记录、PDF和本地文件。
steipete
youtube-summarizer
Extract transcripts from YouTube videos and generate comprehensive, detailed summaries using intelligent analysis frameworks
sickn33
vss-summarize-video
Use to summarize a recorded video via the LVS summarization microservice (HITL-gated) with a VLM fallback. Not for report generation or live RTSP captioning.
nvidia
mantis-summarize
Pre-processes the repository by generating security-focused summaries (mantis-summary.md) for each directory to make planning and research more efficient. Use when starting a review campaign to map the codebase before threat modeling and planning. Don't use for executing code reviews, writing test scripts, or patching code.
google
csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
coffeefuelbump
git-summarize-weekly
Summarize weekly GitHub contributions for writing weekly reports
zc277584121model-usage
Summarize CodexBar local cost logs by model for Codex or Claude, including current or full breakdowns.
openclawmodel-usage
按模型汇总 CodexBar 本地成本日志，适用于 Codex 或 Claude，支持当前或完整明细。
steipete
google-workspace-ops
Operate across Google Drive, Docs, Sheets, and Slides as one workflow surface for plans, trackers, decks, and shared documents. Use when the user needs to find, summarize, edit, migrate, or clean up Google Workspace assets without dropping to raw tool calls.
affaan-mgoogle-workspace-ops
在 Google Drive、Docs、Sheets 和 Slides 中统一操作，将计划、追踪器、演示文稿和共享文档整合为一个工作流界面。当用户需要查找、总结、编辑、迁移或清理 Google Workspace 资产，而无需直接调用底层工具时使用。
affaan-m
claude-api
Claude API / Anthropic SDK 权威参考手册 —— 涵盖模型 ID、计费价格、参数设置、流式传输、工具调用 (tool use)、MCP、Agent 开发、缓存机制 (caching)、Token 统计以及模型迁移。 触发条件 —— 在打开目标文件之前先阅读本文件；切勿因其“看似只有一行”而跳过 —— 当满足以下任意情况时触发：提示词中包含任何形式的 Claude/Anthropic 名称（如 Claude、Anthropic、Fable、Opus、Sonnet、Haiku、`anthropic`、`@anthropic-ai`、`claude-*`、`us.anthropic.*`、`[1m]`）；用户咨询大模型相关问题（如价格、模型选择、额度限制、缓存）—— 严禁仅凭记忆回答；或者任务属于大模型范畴且未明确供应商（如 agent/MCP/工具定义/多 Agent 协同/RAG/LLM 评估/Computer Use；基于自然语言生成/总结/提取/分类/改写/对话；排查拒答、截断、流式传输、工具调用、Token 问题）。 跳过条件 —— 仅当明确使用其他供应商时跳过（优先级高于所有触发条件）：用户提问中提到了 OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama；或者对项目执行 `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` 找到了匹配项（如果用户未指定供应商，请先执行该 grep 命令 —— 切勿直接读取文件）。
anthropics
bmad-sprint-planning
Check that planning is complete enough to implement, then generate the sprint status file from the epics. Can also summarize sprint progress and validate or repair the tracking file. Use when the user says "run sprint planning", "generate sprint plan", "check implementation readiness", "show sprint status", "validate sprint status", or "fix sprint status"
bmad-code-org
product-skills
Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).
alirezarezvani
baoyu-wechat-summary
使用本地 wx-cli 二进制文件（https://github.com/jackwener/wx-cli）提取微信群聊精华并生成结构化简报。默认生成常规简报，可按需生成毒舌（roast）版本。支持跨运行维护每个群的历史记录（history.json + history-digests.jsonl）、群友画像，以及群级事实记忆（memory.md），并内置隐私安全防护。当用户要求“总结群聊”、“群聊精华”、“群聊摘要”、“summarize group chat”、“group chat digest”，或者提到微信群名并附带时间范围，或者说“帮我看看 XX 群最近聊了什么”、“XX 群有什么值得看的”，抑或要求“回溯画像”、“初始化画像”、“backfill profiles”时使用。当用户提到“毒舌版”、“roast 版”、“再来个毒舌的”或类似表述时，附带生成毒舌版本。
jimliu
context-mode
Use context-mode tools (ctx_execute, ctx_execute_file) instead of Bash/cat when processing large outputs. Triggers: "analyze logs", "summarize output", "process data", "parse JSON", "filter results", "extract errors", "check build output", "analyze dependencies", "process API response", "large file analysis", "page snapshot", "browser snapshot", "DOM structure", "inspect page", "accessibility tree", "Playwright snapshot", "run tests", "test output", "coverage report", "git log", "recent commits", "diff between branches", "list containers", "pod status", "disk usage", "fetch docs", "API reference", "index documentation", "call API", "check response", "query results", "find TODOs", "count lines", "codebase statistics", "security audit", "outdated packages", "dependency tree", "cloud resources", "CI/CD output". Also triggers on ANY MCP tool output that may exceed 20 lines. Subagent routing is handled automatically via PreToolUse hook.
mksgludatalineage-summary
Summarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).
googlebigquery-ai-ml
利用 BigQuery 内置的机器学习与生成式 AI（GenAI）能力进行高级数据分析。适用于编写 SQL 查询以实现时间序列预测、数值预测、异常检测、关键驱动因素分析、语义搜索或向量检索、文本分类、相似度计算、内容摘要生成、语言翻译、模型评估、按语义条件过滤，以及在 BigQuery 中调用生成式 AI 能力等场景。请勿用于处理常规的 BigQuery 数据集、数据表或作业管理需求。
google
huggingface-papers
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
huggingface
read
读取URL和PDF，通过获取源内容，默认对纯读取请求返回简洁摘要，当要求转换、保存、引用、引用或为下游工作提供内容时返回干净的Markdown。当用户以任何语言要求读取、获取、检查、总结、引用、引用、转换或保存URL或PDF时使用。不适用于仓库中已有的本地文本文件。
tw93nemo-mbridge-perf-moe-dispatcher-selection
Choose the right MoE token dispatcher (`alltoall`, DeepEP, or HybridEP) for the hardware, EP degree, and optimization stage. Summarizes patterns from DSV3, Qwen3, Qwen3-Next, and VLM bring-up work.
nvidiavss-search-archive
Use this skill to run top-level VSS fusion search on archived video, or to ingest video files / RTSP streams for search. Do NOT use for ad-hoc visual Q&A (use vss-ask-video), live captioning (use vss-deploy-dense-captioning), or video summarization and reports (use vss-summarize-video).
nvidia
use-tinyfish
使用 TinyFish 进行网络搜索、获取 URL、阅读页面、获取最新信息、基于来源的答案、研究、文档、定价/产品页面、提取、抓取和浏览器自动化。当用户要求搜索、查找、查询、研究、比较、从网络获取信息、总结 URL、获取页面内容或自动化网站时使用。
tinyfish-io
meeting-minutes-taker
Transforms raw meeting transcripts into high-fidelity, structured meeting minutes (notes / summaries). Use when (1) a meeting transcript is provided and meeting minutes, notes, or a summary are requested; (2) multiple versions of minutes must be merged without losing content; (3) existing minutes need review against the original transcript for missing items; (4) the transcript has anonymous speakers like "Speaker 1/2/3" or "发言人1" that need identifying (optionally mapped via a context.md team directory). Triggers on 会议纪要 / 会议记录 / 整理纪要 / 妙记转纪要, "write meeting minutes", "summarize this meeting", "merge these minutes", "what's missing from these notes". For fixing ASR/STT recognition errors in the raw transcript first, use transcript-fixer; this skill structures clean transcripts into minutes.
daymade